Book Image

Matplotlib for Python Developers - Second Edition

By : Aldrin Yim, Claire Chung, Allen Yu
Book Image

Matplotlib for Python Developers - Second Edition

By: Aldrin Yim, Claire Chung, Allen Yu

Overview of this book

Python is a general-purpose programming language increasingly being used for data analysis and visualization. Matplotlib is a popular data visualization package in Python used to design effective plots and graphs. This is a practical, hands-on resource to help you visualize data with Python using the Matplotlib library. Matplotlib for Python Developers, Second Edition shows you how to create attractive graphs, charts, and plots using Matplotlib. You will also get a quick introduction to third-party packages, Seaborn, Pandas, Basemap, and Geopandas, and learn how to use them with Matplotlib. After that, you’ll embed and customize your plots in third-party tools such as GTK+3, Qt 5, and wxWidgets. You’ll also be able to tweak the look and feel of your visualization with the help of practical examples provided in this book. Further on, you’ll explore Matplotlib 2.1.x on the web, from a cloud-based platform using third-party packages such as Django. Finally, you will integrate interactive, real-time visualization techniques into your current workflow with the help of practical real-world examples. By the end of this book, you’ll be thoroughly comfortable with using the popular Python data visualization library Matplotlib 2.1.x and leveraging its power to build attractive, insightful, and powerful visualizations.
Table of Contents (16 chapters)
Title Page
Dedication
Packt Upsell
Contributors
Preface
Index

More native Matplotlib plot types


Besides the most basic scatter and line plots, Matplotlib provides a versatile collection of plot types to serve different data visualization purposes. In this section, we will introduce the rationale of plot type selection and the usage of each type.

Choosing the right plot

A successful visualization must communicate the message well. In order to achieve this goal, we need to have a good understanding of the nature of our data as well as the advantages and limitations of each plot type in illustrating different relationships in data. In choosing the right plot type to display, we have the following considerations:

  • Number of variables
  • Distribution of data
  • Relationships between data series

Histogram

Histograms are useful in surveying the distribution of data. For example, we can plot data on a histogram when we want to see some age groups distributed in a population, light exposure in a photograph, or the amount of precipitation in each month in a city.

In Matplotlib...